They delve into the effective implementation of learning for business excellence and recommend treating it like cooking, where various ingredients come together to create something special. They encourage embracing new things and constantly striving to surpass the average or standard. Jan (LinkedIn-Profile) and Daniel (LinkedIn-Profile) advocate for making learning more impactful and identify re- and up-skilling as the main trend in the face of significant transformation. They see it as a crucial step to participate in economic and societal value creation. However, companies should avoid chasing trends and instead focus on strong execution rather than just conceptualization.

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The current main trend is re- and up-skilling

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Nevertheless, the triad of ChatGPT, artificial intelligence, and skill orientation are the parameters to ensure organizational sustainability. Artificial intelligence will transform learning into a dialogue-based approach, a new trend based on the Socratic tradition of dialogue. As the half-life of knowledge has decreased from an average of 30 years to 5-6 years, and even as low as 2 years in IT topics, continuous organizational and personal development has become vital for survival. Whether we like it or not, artificial intelligence will lead to the elimination of job roles. Re- and up-skilling is the answer to keep up with the market and new technologies. To succeed, individuals need to strengthen, demand, and expand their self-learning abilities. Personal relevance and interests form an important foundation in this process. However, due to data protection concerns, such information is often not known in Germany.

Data protection must not prevent meaningful developments

This presents a critical situation given the current challenges. A future-oriented organization requires information about the current skills of its employees. Simultaneously, the annual increase in knowledge should be planned and measured. One of the major challenges faced by competency management is the timeliness and completeness of available data. The rule "Shit in, Shit out" also applies here. Therefore, organizations need an adaptive competency management system that automatically updates information from within and outside the organization. This allows for the creation of adaptive learning paths, forming the basis for data-driven learning.

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Adaptive Competency Management for Data-driven Learning

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Jan and Daniel encourage the development of approaches to use skill management in line with data protection regulations and data ethics. They suggest that personnel development (PD) should have more room for experimentation. The analogy of urban gardening and a flower meadow is drawn to illustrate a future-oriented learning culture that can flourish and thrive within companies. PD should provide the fertile ground and help break down barriers, but not take full control, leaving space for user-generated content. At the same time, robots serve as diligent assistants, coexisting with humans to manage this garden, handle routine tasks, make suggestions, and create new arrangements. Then, in autumn and winter, they uproot, plow, and plan for the upcoming year.

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Management Board should ask specific questions

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The management board and executives also have a crucial role to play. They should ask specific analytical questions related to learning to determine which information and data are truly needed. Skill management with re- and up-skilling begins with the management team. Every CEO is simultaneously the Chief Learning Officer. Only by doing so can learning be implemented as a crucial factor for sustainable competitiveness within organizations. The two experts predict that without skill transparency and skill orientation, organizations won't be able to meet upcoming market dynamics. In this context, both technology and artificial intelligence will be indispensable.